Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: analyzing, by a computing system, messages generated by a plurality of computing devices associated with a plurality of users in a messaging system to extract media content items from the messages and generate training data; training, by the computing system, a machine learning model using the generated training data comprising the media content items to determine a probability that a media content item was generated inside an enclosed location or outside; receiving, by the computing system, a media content item from a computing device; extracting image features from the media content item; analyzing the extracted image features of the media content item to determine objects associated with each extracted image feature; generating a feature vector based on the determined objects associated with each extracted image feature; analyzing the feature vector using the trained machine learning model to determine a probability that the media content item was generated inside an enclosed location or outside; determining, based on the probability generated by the trained machine learning model, that the media content item was generated inside an enclosed location; determining a location of the computing device when the media content item was generated; determining a venue associated with the location of the computing device; determining an inside temperature associated with the venue based on the messages generated by a plurality of computing devices in a messaging system comprising media content items and temperature information for the venue or a similar venue type; generating creative functionality associated with the inside temperature and the venue or similar venue type; and providing the creative functionality to the computing device.
This invention relates to a method for determining whether a media content item was generated inside an enclosed location or outside, and using that determination to provide context-aware creative functionality. The method involves analyzing messages from multiple computing devices in a messaging system to extract media content items and generate training data. A machine learning model is trained using this data to predict whether a media content item was captured indoors or outdoors. When a new media content item is received, image features are extracted, and objects within the image are identified to generate a feature vector. The trained model analyzes this vector to determine the likelihood of the media content item being indoors or outdoors. If the model determines the content was generated inside an enclosed location, the system further determines the device's location, identifies the associated venue, and estimates the inside temperature based on historical data from similar venues. Using this information, the system generates and provides creative functionality tailored to the venue and temperature conditions. The approach leverages machine learning and contextual data to enhance user experience in messaging systems by delivering relevant, location- and environment-aware features.
2. The method of claim 1 , wherein the creative functionality is presented to a user of the computing device to use to augment the media content item or generate a new media content item.
3. The method of claim 1 , wherein the media content item is a first media content item and the computing device is a first computing device, and the method further comprises: receiving a second media content item from a second computing device; extracting image features from the second media content item; analyzing the extracted image features of the second media content item to determine objects associated with each extracted image feature; generating a feature vector based on the determined objects associated with each extracted image feature; analyzing the feature vector using the trained machine learning model to determine a probability that the second media content item was generated inside an enclosed location or outside; determining, based on the probability generated by the trained machine learning model, that the media content item was generated outside; determining at least one outside weather condition associated with a location of the computing device; generating creative functionality associated with the at least one outside weather condition and location of the computing device; and providing the creative functionality to the computing device.
4. The method of claim 1 , further comprising: requesting venue information and inside temperature information associated with a media content item from a plurality of computing devices generating messages; and storing the venue information in one or more databases; wherein determining an inside temperature associated with the venue based on messages generated by a plurality of computing devices in a messaging system comprising media content items and temperature information for the venue or a similar venue type comprises accessing the one or more databases to determine a venue or similar venue type in the one or more databases and determining an average temperature for the venue or similar venue type.
This invention relates to a system for determining and utilizing venue-specific temperature data in a messaging platform. The problem addressed is the lack of accurate, real-time temperature information for venues where media content is consumed, which can impact user experience and content delivery decisions. The system collects venue information and inside temperature data from multiple computing devices within a messaging system that includes media content items and temperature readings. The collected data is stored in one or more databases. When determining the inside temperature for a specific venue or a similar venue type, the system accesses these databases to identify matching or comparable venues and calculates an average temperature based on the stored data. This allows for more accurate temperature assessments, which can be used to optimize content delivery, improve user comfort predictions, or enhance venue-specific services. The method ensures that temperature data is dynamically updated and refined as more messages and data points are received from users across different venues.
5. The method of claim 1 , wherein determining the inside temperature associated with the venue is further based on a time of day.
A system and method for monitoring and controlling environmental conditions within a venue, such as a building or enclosed space, to optimize energy efficiency and occupant comfort. The system addresses the challenge of accurately determining and adjusting the internal temperature of a venue based on dynamic factors, including external weather conditions and time of day. The method involves collecting real-time data from sensors placed inside and outside the venue to assess environmental conditions. The inside temperature is calculated by analyzing this data, incorporating the time of day to account for variations in solar radiation, occupancy patterns, and other time-dependent factors. By integrating time-based adjustments, the system improves temperature regulation precision, reducing energy consumption while maintaining comfort. The method may also include adjusting HVAC systems or other climate control mechanisms based on the calculated temperature and time-dependent factors. This approach ensures that the venue's internal environment is optimized for both efficiency and comfort throughout the day.
6. The method of claim 1 , wherein generating the training data comprises selecting a first subset of the media content items representing media content items generated inside an enclosed location and a second subset of media content items representing media content items generated outside.
This invention relates to generating training data for machine learning models used in media content analysis, particularly for distinguishing between media content captured inside enclosed locations (e.g., indoors) and outside (e.g., outdoors). The problem addressed is the need for accurate training data to improve the performance of models that classify or analyze media content based on its environmental context. The method involves selecting a first subset of media content items that were generated inside enclosed locations, such as buildings or vehicles, and a second subset generated outside, such as in open spaces or natural environments. These subsets are used to train machine learning models to recognize distinguishing features between indoor and outdoor media content. The training data may include images, videos, or audio recordings, and the selection process ensures a balanced representation of both environments to improve model accuracy. The method may also involve preprocessing the media content, such as extracting features or labeling data, to enhance training efficiency. The goal is to enable more reliable classification of media content based on its environmental context, which can be applied in various applications, including surveillance, content moderation, and automated tagging.
7. The method of claim 6 , wherein selecting the first subset of media content items and the second subset of media content items is based on an indication in each of the messages associated with each media content item indicating that the media content item was generated inside an enclosed location or outside.
Digital content management and display. This invention addresses the need to selectively present media content based on its origin. The method involves receiving messages, each associated with a media content item. An indication within each message specifies whether the corresponding media content item was generated inside an enclosed location or outside. Based on this inside/outside indication, a first subset of media content items is selected, and a second subset of media content items is also selected. These subsets are then utilized in a downstream process, presumably for presentation or further processing. The core functionality lies in categorizing and segmenting media content based on its environmental generation context as communicated through associated metadata.
8. The method of claim 7 , wherein the indication was input by a user sending the message.
A system and method for message processing and indication handling in communication networks. The invention addresses the challenge of efficiently managing message indications, such as read receipts or delivery confirmations, in digital communication systems. The method involves detecting an indication associated with a message, where the indication is generated by a user who sent the message. The indication may include metadata such as timestamps, status flags, or user-specific annotations. The system processes this indication to update the message status, trigger notifications, or log the event in a communication history. The method ensures that user-generated indications are accurately captured and integrated into the communication workflow, improving transparency and reliability in message exchanges. The invention may be applied in email systems, instant messaging platforms, or enterprise collaboration tools where message tracking and user feedback are critical. The solution enhances user experience by providing clear visibility into message handling and reducing ambiguity in communication status.
9. The method of claim 1 , further comprising: receiving an indication that the creative functionality was utilized by the computing device or was not used by the computing device; storing the indication as validation data associated with the venue; and using the validation data to determine if the inside temperature determined for the venue was correct.
This invention relates to a system for validating temperature measurements in a venue using creative functionality, such as augmented reality (AR) or virtual reality (VR), to engage users in temperature data collection. The system addresses the challenge of accurately determining indoor temperatures in venues where traditional sensors may be unreliable or unavailable. The method involves deploying a computing device, such as a smartphone or AR/VR headset, to a user within the venue. The device presents creative content, such as an interactive game or AR overlay, that encourages the user to move around the venue. As the user interacts with the content, the device collects environmental data, including temperature readings, from its sensors. The system then processes this data to determine an inside temperature for the venue. Additionally, the system receives feedback indicating whether the creative functionality was utilized by the user or not. This feedback is stored as validation data linked to the venue and used to assess the accuracy of the temperature determination. By leveraging user engagement through creative interactions, the system improves the reliability of temperature measurements in indoor environments.
10. A system comprising: a memory that stores instructions; and one or more hardware processors configured by the instructions to perform operations comprising: analyzing messages generated by a plurality of computing devices associated with a plurality of users in a messaging system to extract media content items from the messages and generate training data; training a machine learning model using the generated training data comprising the media content items to determine a probability that a media content item was generated inside an enclosed location or outside; receiving a media content item from a computing device; extracting image features from the media content item; analyzing the extracted image features of the media content item to determine objects associated with each extracted image feature; generating a feature vector based on the determined objects associated with each extracted image feature; analyzing the feature vector using the trained machine learning model to determine a probability that the media content item was generated inside an enclosed location or outside; determining, based on the probability generated by the trained machine learning model, that the media content item was generated inside an enclosed location; determining a location of the computing device when the media content item was generated; determining a venue associated with the location of the computing device; determining an inside temperature associated with the venue based on messages generated by a plurality of computing devices in a messaging system comprising media content items and temperature information for the venue or a similar venue type; generating creative functionality associated with the inside temperature and the venue or similar venue type; and providing the creative functionality to the computing device.
This invention relates to a system for determining whether a media content item, such as an image or video, was captured inside an enclosed location (e.g., a building) or outside, and using that determination to provide context-aware functionality. The system addresses the challenge of accurately identifying indoor versus outdoor environments based on media content, which is useful for applications like location-based services, advertising, or environmental monitoring. The system analyzes messages from multiple users in a messaging system to extract media content items and generate training data. A machine learning model is trained on this data to predict whether a media content item was captured indoors or outdoors. When a new media content item is received, the system extracts image features, identifies objects within the image, and generates a feature vector. The trained model analyzes this vector to determine the likelihood of an indoor or outdoor setting. If the system determines the media content item was captured indoors, it further identifies the device's location, the associated venue (e.g., a restaurant or office), and retrieves the inside temperature for that venue or similar venues based on historical messaging data. The system then generates and provides creative functionality—such as targeted content, recommendations, or notifications—tailored to the indoor environment and temperature conditions. This approach enhances user experience by delivering contextually relevant information based on the physical setting of the media content.
11. The system of claim 10 , wherein the creative functionality is presented to a user of the computing device to use to augment the media content item or generate a new media content item.
This invention relates to a computing system that enhances media content creation by integrating creative functionality. The system addresses the challenge of providing users with intuitive tools to modify or generate media content, such as images, videos, or audio, by embedding creative features directly within the computing environment. The system includes a computing device with a display and input mechanisms, along with software that processes media content items. The creative functionality, which may include filters, effects, editing tools, or generative AI capabilities, is dynamically presented to the user based on the context of the media content. The system allows users to apply these features to existing media or create entirely new content. The creative tools are designed to be user-friendly, ensuring accessibility for both novice and experienced users. The system may also adapt the available functionalities based on user preferences or the type of media being processed, optimizing the creative workflow. By integrating these tools seamlessly, the system streamlines the content creation process, reducing the need for external applications or complex workflows. The invention aims to empower users to produce high-quality, customized media efficiently.
12. The system of claim 10 , wherein the media content item is a first media content item and the computing device is a first computing device, and the operations further comprise: receiving a second media content item from a second computing device; extracting image features from the second media content item; analyzing the extracted image features of the second media content item to determine objects associated with each extracted image feature; generating a feature vector based on the determined objects associated with each extracted image feature; analyzing the feature vector using the trained machine learning model to determine a probability that the second media content item was generated inside an enclosed location or outside; determining, based on the probability generated by the trained machine learning model, that the media content item was generated outside; determining at least one outside weather condition associated with a location of the computing device; generating creative functionality associated with the at least one outside weather condition and location of the computing device; and providing the creative functionality to the computing device.
This invention relates to a system for analyzing media content to determine its generation environment and providing context-aware creative functionality. The system processes media content items, such as images or videos, to detect whether they were captured indoors or outdoors. It extracts image features from the media content, identifies objects within those features, and generates a feature vector representing the detected objects. A trained machine learning model analyzes this feature vector to determine the likelihood that the media content was generated inside an enclosed location or outside. If the system determines the content was captured outdoors, it identifies weather conditions at the device's location and generates creative functionality tailored to those conditions and location. This functionality could include filters, effects, or other enhancements relevant to the outdoor environment and weather. The system then provides this creative functionality to the user's device, enhancing the user experience by offering contextually appropriate tools. The invention improves media editing and creation by automatically adapting to the environment in which the content was captured.
13. The system of claim 10 , the operations further comprising: requesting venue information and inside temperature information associated with a media content item from a plurality of computing devices generating messages; and storing the venue information in one or more databases; wherein determining an inside temperature associated with the venue based on messages generated by a plurality of computing devices in a messaging system comprising media content items and temperature information for the venue or a similar venue type comprises accessing the one or more databases to determine a venue or similar venue type in the one or more databases and determining an average temperature for the venue or similar venue type.
This invention relates to a system for determining inside temperatures of venues based on data collected from computing devices in a messaging system. The problem addressed is the lack of accurate, real-time temperature data for venues, which is useful for applications like media content delivery, event planning, or environmental monitoring. The system collects venue information and temperature data from multiple computing devices that generate messages containing media content items and temperature readings. The system stores this data in one or more databases. When determining the inside temperature of a venue, the system accesses the databases to identify the venue or a similar venue type and calculates an average temperature based on the stored data. This approach leverages crowdsourced temperature information to provide more accurate and context-aware temperature estimates for venues, improving decision-making in applications that rely on environmental data. The system may also use the collected venue information for additional purposes, such as enhancing media content delivery or optimizing venue management.
14. The system of claim 10 , wherein determining the inside temperature associated with the venue is further based on a time of day.
This invention relates to a system for monitoring and determining the inside temperature of a venue, such as a building or enclosed space, to optimize energy efficiency and comfort. The system addresses the challenge of accurately assessing indoor temperature conditions, which can vary due to external factors like weather, occupancy, and time of day. The system includes sensors for measuring environmental conditions, such as temperature and humidity, and processes this data to calculate the inside temperature. The system also accounts for the time of day to refine temperature determinations, ensuring more precise adjustments to heating, ventilation, and air conditioning (HVAC) systems. By integrating time-based data, the system improves energy management by aligning temperature control with daily usage patterns, reducing unnecessary energy consumption. The system may also incorporate historical temperature data and external weather conditions to enhance accuracy. The overall goal is to provide a dynamic and responsive temperature monitoring solution that adapts to real-time and time-dependent variations, improving both energy efficiency and occupant comfort.
15. The system of claim 10 , wherein generating the training data comprises selecting a first subset of the media content items representing media content items generated inside an enclosed location and a second subset of media content items representing media content items generated outside.
This invention relates to a system for generating training data for machine learning models, particularly for analyzing media content items based on their geographic context. The problem addressed is the need for accurate training data that distinguishes between media content generated inside enclosed locations (e.g., buildings, vehicles) and outside (e.g., open environments). The system selects a first subset of media content items captured or generated within enclosed locations and a second subset from outdoor environments. These subsets are used to train models to classify or analyze media content based on its spatial context. The system may also include preprocessing steps to extract features from the media content, such as audio, video, or sensor data, to improve classification accuracy. The training data generation process ensures that the model can reliably differentiate between indoor and outdoor media content, which is useful for applications like surveillance, content moderation, or contextual advertising. The system may further incorporate metadata, such as GPS or timestamp data, to enhance the training process. By leveraging distinct subsets of media content, the system improves the robustness of machine learning models in recognizing and processing location-specific content.
16. The system of claim 15 , wherein selecting the first subset of media content items and the second subset of media content items is based on an indication in each of the messages associated with each media content item indicating that the media content item was generated inside an enclosed location or outside.
This invention relates to a system for organizing and displaying media content items, such as images or videos, based on their geographic context. The problem addressed is the difficulty in automatically categorizing and presenting media content in a meaningful way, particularly when the content was captured in different environments like indoors or outdoors. The system processes media content items associated with messages, where each message includes metadata indicating whether the content was generated inside an enclosed location (e.g., indoors) or outside (e.g., outdoors). The system selects a first subset of media content items marked as generated inside enclosed locations and a second subset marked as generated outside. These subsets are then displayed separately or in a structured manner, allowing users to easily distinguish between indoor and outdoor content. The system may further analyze the media content items to verify or refine the location-based classification, ensuring accuracy. Additionally, the system can prioritize or filter the display of content based on user preferences, time of capture, or other metadata. This approach enhances user experience by providing contextually relevant organization of media content.
17. The system of claim 16 , wherein the indication was input by a user sending the message.
A system for message processing and user interaction in communication platforms addresses the challenge of efficiently managing and responding to user inputs within digital messaging environments. The system includes a message processing module that receives and analyzes messages sent by users, extracting relevant data such as sender information, message content, and contextual metadata. A user interaction module interprets these inputs to determine the appropriate system response, which may include generating automated replies, updating user profiles, or triggering specific actions within the platform. The system further incorporates a feedback mechanism that allows users to provide explicit or implicit feedback on the system's responses, enabling continuous improvement of the interaction logic. In this specific embodiment, the system is configured to recognize and process indications that were explicitly input by the user sending the message, ensuring that user-intended actions or preferences are accurately captured and acted upon. This feature enhances the system's ability to distinguish between automated and user-driven inputs, improving the accuracy and relevance of responses. The system may be integrated into various communication platforms, including social media, messaging apps, or customer support systems, to streamline user interactions and enhance overall platform functionality.
18. The system of claim 10 , the operations further comprising: receiving an indication that the creative functionality was used by the computing device or was not used by the computing device; storing the indication as validation data associated with the venue; and using the validation data to determine if the inside temperature determined for the venue was correct.
This invention relates to a system for validating temperature measurements in venues, particularly where creative functionality (such as interactive displays or sensors) is used to determine indoor temperatures. The problem addressed is ensuring the accuracy of temperature readings in venues where environmental conditions may be influenced by user interactions or dynamic elements. The system receives data indicating whether creative functionality was used by a computing device within the venue. This usage data is stored as validation data linked to the venue. The system then analyzes this validation data to assess whether the recorded indoor temperature for the venue is accurate. For example, if creative functionality (such as heating or cooling elements) was active, the system may adjust or confirm the temperature reading accordingly. If the functionality was unused, the system may rely on baseline measurements or alternative validation methods. The system may also compare the validation data against historical or external temperature records to further verify accuracy. This approach ensures that temperature readings are reliable, even in environments where user interactions or dynamic elements could otherwise introduce errors. The invention is particularly useful in venues like museums, event spaces, or interactive exhibits where environmental conditions are influenced by user engagement.
19. A non-transitory computer-readable medium comprising instructions stored thereon that are executable by at least one processor to cause a computing device to perform operations comprising: a memory that stores instructions; and one or more hardware processors configured by the instructions to perform operations comprising: analyzing messages generated by a plurality of computing devices associated with a plurality of users in a messaging system, to extract media content items from the messages and generate training data; training a machine learning model using the generated training data comprising the media content items to determine a probability that a media content item was generated inside an enclosed location or outside; receiving a media content item from a computing device; extracting image features from the media content item; analyzing the extracted image features of the media content item to determine objects associated with each extracted image feature; generating a feature vector based on the determined objects associated with each extracted image feature; analyzing the feature vector using the trained machine learning model to determine a probability that the media content item was generated inside an enclosed location or outside; determining, based on the probability generated by the trained machine learning model, that the media content item was generated inside an enclosed location; determining a location of the computing device when the media content item was generated; determining a venue associated with the location of the computing device; determining an inside temperature associated with the venue based on messages generated by a plurality of computing devices in a messaging system comprising media content items and temperature information for the venue or a similar venue type; generating creative functionality associated with the inside temperature and the venue or similar venue type; and providing the creative functionality to the computing device.
This invention relates to a system for analyzing media content items, such as images or videos, to determine whether they were captured inside an enclosed location (e.g., a building) or outside. The system extracts media content from user messages in a messaging system to generate training data for a machine learning model. The model is trained to classify media content based on extracted image features, identifying objects within the content to generate a feature vector. When a new media content item is received, the system analyzes its features to determine the likelihood it was taken indoors or outdoors. If classified as indoors, the system further determines the device's location, identifies the associated venue (e.g., a restaurant or office), and estimates the inside temperature based on historical data from similar venues. Using this information, the system generates and provides creative functionality, such as contextual suggestions or notifications, tailored to the venue and temperature conditions. The approach leverages user-generated content to enhance contextual awareness in messaging systems.
20. The non-transitory computer-readable medium of claim 19 , wherein the media content item is a first media content item and the computing device is a first computing device, and the operations further comprise: receiving a second media content item from a second computing device; extracting image features from the second media content item; analyzing the extracted image features of the second media content item to determine objects associated with each extracted image feature; generating a feature vector based on the determined objects associated with each extracted image feature; analyzing the feature vector using the trained machine learning model to determine a probability that the second media content item was generated inside an enclosed location or outside; determining, based on the probability generated by the trained machine learning model, that the media content item was generated outside; determining at least one outside weather condition associated with a location of the computing device; generating creative functionality associated with the at least one outside weather condition and location of the computing device; and providing the creative functionality to the computing device.
This invention relates to a system for analyzing media content to determine its generation environment and providing context-aware creative functionality. The system processes media content items, such as images or videos, to determine whether they were captured indoors or outdoors. A trained machine learning model analyzes extracted image features to identify objects and generate a feature vector, which is used to predict the likelihood of the content being generated in an enclosed or open environment. If the content is determined to be outdoors, the system further identifies weather conditions and the device's location to generate and provide creative functionality tailored to those conditions. For example, if the content was captured outside in rainy weather, the system may suggest filters, effects, or editing tools that enhance or complement the rainy atmosphere. The system operates across multiple devices, allowing it to receive and process media content from different sources while maintaining contextual relevance. This approach enhances user experience by dynamically adapting creative tools based on environmental and situational factors.
Unknown
September 8, 2020
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